Kamran Baveicy1, Shayan Mostafaei2,3, Mitra Darbandi4, Behrooz Hamzeh4,5, Farid Najafi4,6, Yahya Pasdar4,5. 1. Student Research Committee, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran. 2. Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran. 3. Epidemiology and Biostatistics Unit, Rheumatology Research Center, Tehran University of Medical Sciences, Tehran, Iran. 4. Research Center for Environmental Determinants of Health (RCEDH), Health Institute, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran. 5. Social Development and Health Promotion Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran. 6. Cardiovascular Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Abstract
BACKGROUND: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction of MetS. METHODS: This cross-sectional study was performed on 10,000 individuals aged from 35 to 65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort study, in the west region of Iran, in 2019. MetS was defined according to International Diabetes Federation (IDF) criteria. The receiver operating characteristic (ROC) curve analysis was used to assess predictive anthropometric indices and determine optimal cutoff values. RESULTS: The optimal cutoff points for VAI were 4.11 (AUC: 0.82; 95% CI: 0.81-0.84) in men and 4.28 (AUC: 0.86; 95% CI: 0.85-0.87) in women to prediction of MetS. The optimal cutoff points for BRI were 4.75 (AUC: 0.75; 95% CI: 0.74-0.77) in men and 6.17 (AUC: 0.62; 95% CI: 0.61-0.64) in women to prediction of MetS. The optimal cutoff points for ABSI were 0.12 (AUC: 0.49; 95% CI: 0.47-0.51) in men and 0.13 (AUC: 0.49; 95% CI: 0.47-0.51) in women to prediction of MetS. The risk of MetS in men and women with a VAI higher than the optimal cutoff point was, respectively, 9.82 and 11.44 times higher than that in those with a VAI lower than the cutoff point. CONCLUSION: Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS.
BACKGROUND: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction of MetS. METHODS: This cross-sectional study was performed on 10,000 individuals aged from 35 to 65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort study, in the west region of Iran, in 2019. MetS was defined according to International Diabetes Federation (IDF) criteria. The receiver operating characteristic (ROC) curve analysis was used to assess predictive anthropometric indices and determine optimal cutoff values. RESULTS: The optimal cutoff points for VAI were 4.11 (AUC: 0.82; 95% CI: 0.81-0.84) in men and 4.28 (AUC: 0.86; 95% CI: 0.85-0.87) in women to prediction of MetS. The optimal cutoff points for BRI were 4.75 (AUC: 0.75; 95% CI: 0.74-0.77) in men and 6.17 (AUC: 0.62; 95% CI: 0.61-0.64) in women to prediction of MetS. The optimal cutoff points for ABSI were 0.12 (AUC: 0.49; 95% CI: 0.47-0.51) in men and 0.13 (AUC: 0.49; 95% CI: 0.47-0.51) in women to prediction of MetS. The risk of MetS in men and women with a VAI higher than the optimal cutoff point was, respectively, 9.82 and 11.44 times higher than that in those with a VAI lower than the cutoff point. CONCLUSION: Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS.
Authors: K G M M Alberti; Robert H Eckel; Scott M Grundy; Paul Z Zimmet; James I Cleeman; Karen A Donato; Jean-Charles Fruchart; W Philip T James; Catherine M Loria; Sidney C Smith Journal: Circulation Date: 2009-10-05 Impact factor: 29.690
Authors: Martijn F H Maessen; Thijs M H Eijsvogels; Rebecca J H M Verheggen; Maria T E Hopman; André L M Verbeek; Femmie de Vegt Journal: PLoS One Date: 2014-09-17 Impact factor: 3.240